Single-Channel Sparse Non-Negative Blind Source Separation Method for Automatic 3-D Delineation of Lung Tumor in PET Images

Author:

Kopriva IvicaORCID,Ju Wei,Zhang Bin,Shi Fei,Xiang Dehui,Yu Kai,Wang Ximing,Bagci Ulas,Chen XinjianORCID

Funder

“Dealination of lung tumor though nonlinear decomposition of PET/CT image;”

Croatian Science Foundation

“Structured Decompositions of Empirical Data for Computationally-Assisted Diagnoses of Disease;”

National Basic Research Program of China (973 Program)

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Biotechnology

Cited by 13 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Current progress and future perspectives in total‐body PET imaging, part I: Data processing and analysis;iRADIOLOGY;2024-03-11

2. Non-Negative Matrix Underapproximation as Optimal Frequency Band Selector;IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society;2023-10-16

3. Blind signal separation based on signal minimum projection;Second International Symposium on Computer Applications and Information Systems (ISCAIS 2023);2023-06-26

4. Small cell lung tumour differentiation using F-18 (Fluorine-18) PET and smoothing using Gaussian 3D convolution operator;International Journal of Nanotechnology;2023

5. Application of non-negative matrix factorization in oncology: one approach for establishing precision medicine;Briefings in Bioinformatics;2022-07-05

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